ethmodlab Goto Github PK

ai-on-a-chip

This code was written for the publication "Combining generative artificial intelligence and on-chip synthesis for de novo drug design"

bcpaff

Exploring protein-ligand binding affinity prediction with electron density-based geometric deep learning

bimodal

Supporting code for the paper "Bidirectional Molecule Generation with Recurrent Neural Networks" (J. Chem. Inf. 2020, 60, 3).

clm_perplexity

compress_fingerprints

Autoencoder compression of fingerprints

de_novo_design_rnn

Code for "De novo molecular design with chemical language models"

delfta

Δ-QML for medicinal chemistry

dragonfly_gen

De novo drug design with deep interactome learning

ethmodlab.github.io

hybridclms

Supporting code for the paper «Leveraging molecular structure and bioactivity with chemical language models for drug design»

lsfml

Enabling late-stage drug diversification by high-throughput experimentation with geometric deep learning

lstm_peptides

Long short-term memory recurrent neural networks for learning peptide and protein sequences to later design new, similar examples.

minisci

Identifying opportunities for late-stage C-H alkylation with in silico reaction screening and high-throughput experimentation

modlab_pages_theme

modlamp

Python package for peptide sequence generation, peptide descriptor calculation and sequence analysis.

molecular_design_with_beam_search

molgrad

Coloring molecules with explainable artificial intelligence

rescoss_logp_ml

rna_binding

Translating from Proteins to Ribonucleic Acids for Ligand-Binding Site Detection

scaffold_hopping_whales

Code to perform scaffold hopping and virtual screening using WHALES descriptors.

virtual_libraries

Supporting code for the paper «Generative molecular design in low data regimes»

whales_descriptors

python code for calculating the WHALES (Weighted Holistic Atom Localization and Entity Shape) molecular descriptors